JP2022104766A - Apnea detection electronic device and apnea detection method - Google Patents

Abstract

To provide an apnea detection electronic device and an apnea detection method.SOLUTION: An apnea detection method includes the steps of: sending a radio signal to a subject, receiving an echo corresponding to the radio signal, and obtaining channel state information (CSI) from the echo signal; generating a detection result in accordance with the CSI; and outputting the detection result. In this case, the detection result indicates whether the phenomenon of apnea is occurring to the subject.SELECTED DRAWING: Figure 6

Description

The present invention relates to an apnea detection electronic device and an apnea detection method.

Statistics show that many patients around the world suffer from apnea, but only some of these patients are treated. Apnea can adversely affect the patient's health and quality of life. For example, patients with apnea tend to snore during sleep, which can interfere with the sleep of the patient's partner. When a phenomenon (event) of aspiration occurs, the airflow in the patient's airway is completely stopped, which may reduce the patient's blood oxygen concentration. Long-term reductions in blood oxygen levels can lead to Alzheimer's disease.

To test whether a person suffers from apnea, he or she needs to spend the night at the sleep center of the hospital to monitor his or her breathing. If a person's breathing stops for more than 10 seconds, it can be determined that the person is suffering from apnea. However, it is difficult for the average person to receive an expensive sleep center, and it takes a lot of time to visit the sleep center for examination.

In response to the above, certain devices on the market allow users to test for apnea themselves. However, these devices require contact with the user, which either reduces the user's motivation to use the device or adversely affects the user's sleep quality. Moreover, these devices cannot reduce the frequency of apnea phenomena.

The present invention provides an apnea detection electronic device and an apnea detection method that detect whether or not an apnea phenomenon is occurring in a subject by a non-contact method.

In one embodiment of the invention, the apnea detection electronic device comprises a processor, a storage medium, and a transceiver. The storage medium stores a plurality of modules. The processor is coupled to a storage medium and a transceiver to access and execute multiple modules. In this case, these modules include a data acquisition module, a detection module, and an output module. The data acquisition module transmits a radio signal to the subject via the transceiver, receives an echo corresponding to the radio signal via the transceiver, and acquires channel state information (CSI) from the echo. The detection module generates a detection result according to the CSI, and indicates whether or not the subject is experiencing an apnea phenomenon based on the detection result. The output module outputs the detection result via the transceiver.

In one embodiment of the invention, the apnea detection electronic device further comprises an air cushion and an air pump. The air pump is connected to the air cushion and communicates with the transceiver. In this case, the module further includes an air cushion control module. This air cushion control module expands the air cushion by setting the air pump via the transceiver in response to the phenomenon of apnea.

In one embodiment of the present invention, the detection module is further configured to calculate a first-order differential signal corresponding to the CSI and to detect the phenomenon of apnea based on this first-order differential signal.

In one embodiment of the present invention, the detection module is further configured to generate a filtering signal corresponding to the CSI according to the filtering algorithm and to differentiate the filtering signal to generate a first-order differential signal.

In one embodiment of the invention, the filtering algorithm is associated with at least one of moving average filtering, high pass filtering, low pass filtering and band pass filtering.

In one embodiment of the invention, the detection module further generates a plurality of frequency responses corresponding to first-order differential signals so that the plurality of frequency responses correspond to a plurality of time points, respectively, and these plurality of frequency responses. A plurality of maximum values corresponding to each of the above are obtained, a maximum value curve corresponding to the first reference time zone is generated according to these multiple maximum values, and the first reference time zone is a plurality of time points. And is configured to detect the phenomenon of aspiration according to the maximum value curve.

In one embodiment of the present invention, the detection module further extracts a second reference time zone from the first reference time zone according to a threshold value, and the second reference time zone is among a plurality of maximum values. Corresponds to a subset of, making each of the maximums in this subset smaller than the threshold, and in response to a second reference time zone being longer than the aspiration time zone. It is configured to determine that the phenomenon of aspiration has been detected.

In one embodiment of the present invention, the detection module is further arranged by arranging a plurality of maximum values from the smaller one to the larger one to generate a maximum value column, and the Nth maximum value from the maximum value column is squeezed. Selected as a value, this N is configured to be the product of the ratio of the abstinence time zone to the first reference time zone and the number of plurality of maximum values.

In one embodiment of the invention, the detection module further generates upper and lower bounds according to the median of the first derivative signal, with data points greater than or less than the lower bound in the first derivative signal. Is determined as an outlier, and this outlier is corrected to generate a corrected first-order differential signal, and multiple frequency responses are generated according to this corrected first-order differential signal. Configure.

In one embodiment of the invention, the detection module performs interpolation calculations on a step of replacing outliers with medians and a first data point prior to the data points and a second data point after the data points. The outliers are corrected, and the outliers are corrected according to one of the steps of making the first data point and the second data point included in the first-order differential signal. ..

In one embodiment of the invention, the apnea detection method comprises the following steps: transmitting a radio signal to a subject, receiving an echo corresponding to the radio signal, and obtaining a CSI from the echo signal. The detection result is generated and output according to the CSI, and the detection result has a step of indicating whether or not the phenomenon of apnea is occurring in the subject.

In one embodiment of the invention, the apnea detection method further comprises a step of configuring the air pump to inflate the air cushion in response to the phenomenon of apnea.

In one embodiment of the present invention, the step of generating the detection result according to the CSI is the step of calculating the first-order differential signal corresponding to the CSI, and the step of detecting the phenomenon of aspiration according to the first-order differential signal. Have steps and.

In one embodiment of the present invention, the step of calculating the first-order differential signal corresponding to the CSI is the step of generating the filtering signal corresponding to the CSI according to the filtering algorithm, and the step of differentiating the filtering signal to obtain the first-order differential signal. To have a step to generate.

In one embodiment of the invention, the filtering algorithm is associated with at least one of moving average filtering, high pass filtering, low pass filtering and band pass filtering.

In one embodiment of the invention, the step of detecting the phenomenon of aspiration in response to a first-order differential signal produces a plurality of frequency responses corresponding to the first-order differential signal, and these plurality of frequency responses are at multiple time points. A step to make each correspond, a step to acquire a plurality of maximum values corresponding to each of these multiple frequency responses, and a maximum value curve corresponding to the first reference time zone according to these multiple maximum values are generated. Then, the first reference time zone has a step of having a plurality of time points and a step of detecting the phenomenon of aspiration according to the maximum value curve.

In one embodiment of the invention, the step of detecting the phenomenon of apnea according to the maximum value curve extracts the second reference time zone from the first reference time zone according to the threshold value, and the second reference time zone is extracted. A step of ensuring that the reference time zone of is smaller than the threshold value for each of the plurality of maximum values in this subset while corresponding to a subset of the plurality of maximum values, and a second reference time. Have a step to determine to detect the phenomenon of apnea in response to the band being longer than the time of apnea.

In one embodiment of the invention, the step of detecting the phenomenon of apnea according to the maximum value curve is further a step of arranging a plurality of maximum values from small to large to generate a sequence of maximum values. The Nth maximum value from the maximum value column is selected as the threshold value, and this N is the product of the ratio of the apneic time zone to the first reference time zone and the number of multiple maximum values. To have.

In one embodiment of the present invention, the step of generating a plurality of frequency responses corresponding to the first-order differential signal is a step of generating an upper limit value and a lower limit value according to the median value of the first-order differential signal, and a first-order differential signal. The step of determining a data point larger than the upper limit value or smaller than the lower limit value as an outlier, and correcting this outlier to generate a corrected first-order differential signal, and this corrected first-order differential signal. Have a step to generate multiple frequency responses depending on the.

In one embodiment of the invention, the step of correcting the outliers to generate the corrected first-order differential signal is a step of replacing the outliers with the median, and a first data point and data prior to the data points. One of the steps of performing an interpolation calculation on the second data point after the point to update the outliers so that the first and second data points are included in the first-order differential signal. To have the steps of.

Considering the above, the apnea detection electronic device provided in one or more embodiments of the present invention can be applied to detect CSI without contact with the subject, yet is apneic. It is possible to determine if the phenomenon has occurred in the subject. Further, whether or not the apnea detection electronic device provided in one or more embodiments of the present invention applies an air cushion to move the subject's head, thereby avoiding the occurrence of respiratory arrest. Can also be determined.

In order to make the present invention more understandable, some embodiments with reference to the drawings will be described in detail below.

The accompanying drawings are included to deepen the understanding of the present invention, are included in a part of the present specification, and constitute a part of the present specification. These drawings show embodiments of the present invention and, in combination with the description of the present specification, serve to explain the principles of the present invention.

It is a diagram which shows the apnea detection electronic apparatus by one Embodiment of this invention. FIG. 2A is a diagram showing channel state information (CSI) according to an embodiment of the present invention. FIG. 2B is a diagram showing a first-order differential signal according to an embodiment of the present invention. FIG. 2C is a diagram showing a filtering signal according to an embodiment of the present invention. FIG. 2D is a diagram showing a corrected first-order differential signal according to an embodiment of the present invention. It is a diagram for acquiring the maximum value of a frequency response by one Embodiment of this invention. It is a diagram for determining the occurrence of the phenomenon of apnea based on the maximum value by one Embodiment of this invention. It is a diagram for moving the head of a subject using an air cushion according to one embodiment of the present invention. It is a flow chart which shows the apnea detection method by one Embodiment of this invention.

The following detailed description provides many specific details for a complete understanding of the disclosed embodiments for purposes of explanation. However, it is clear that one or more embodiments can be performed without these specific details. In another example, well-known structures and devices are shown graphically to simplify the drawings.

FIG. 1 is a diagram showing an apnea detection electronic device 100 according to an embodiment of the present invention. The electronic device 100 may have a processor 110, a storage medium 120, and a transceiver 130. In one embodiment, the electronic device 100 may further include an air pump 200 and an air cushion 300.

The processor 110 may be, for example, a central processing unit (CPU) or other programmable general purpose or dedicated microcontrol unit (MCU), microprocessor, digital signal processor (DSP), programmable controller, application-specific integrated circuit (ASIC), graphic processing. Unit (GPU), Image Signal (Image Signal) Processor (ISP), Image Processing Unit (IPU), Computational Logic Unit (ALU), Composite Programmable Logic Device (CPLD), Field Programmable Gate Array (FPGA), and more. It is a component or a combination of the above-mentioned components. The processor 110 can be coupled to the storage medium 120 and the transceiver 130, and can execute a plurality of modules and various application programs stored in the storage medium 120.

The storage medium 120 may include, for example, any type of fixed or portable random access memory (RAM), read-only memory (ROM), flash memory, hard disk drive (HDD), solid state drive (SSD), and the like. Other similar components, or a combination of the components described above, the storage medium 120 can be configured to store modules or various application programs that can be executed by the processor 110. In this embodiment, the storage medium 120 can store modules including a data acquisition module 121, a subcarrier selection module 122, a detection module 123, an output module 124 and an air cushion module 125, and the functions of these modules will be described later.

The transceiver 130 sends and receives signals wirelessly or by wire. The transceiver 130 can also perform processing including low noise amplification, impedance matching, frequency mixing, upward or downward frequency conversion, filtering, amplification, and the like. The processor 110 can communicate with the air pump 200 via the transceiver 130.

The air pump 200 is coupled to the air cushion 300. The processor 110 may be provided with an air pump 200 for expanding or contracting the air cushion 300.

To determine if the phenomenon of apnea is occurring in the subject, the data acquisition module 121 sends a radio signal to the subject via the transceiver 130 and an echo corresponding to this radio signal via the transceiver 130. Can be received. This radio signal is, for example, any kind of radio frequency signal (for example, Wi-Fi signal). In one embodiment, the subcarrier selection module 122 may be configured to select a particular subcarrier. Also, the data acquisition module 121 may transmit the radio signal or receive an echo of the radio signal from the selected subcarrier via the transceiver 130. For example, when the radio signal is a Wi-Fi signal, the subcarrier selection module 122 selects either or both of the 3rd to 27th subcarriers and the 39th to 64th subcarriers of the Wi-Fi signal. And can send a radio signal or receive an echo of this radio signal.

The data acquisition module 121 can acquire channel state information (CSI) from the echo after receiving the echo via the transceiver 130. The detection module 123 can generate a detection result indicating whether or not the phenomenon of apnea has occurred in the subject according to this CSI. The output module 124 can output this detection result via the transceiver 130. For example, the output module 124 can transmit this detection result to the user's terminal device (for example, a smartphone). The user can interpret this detection result via the terminal device to determine whether or not the phenomenon of apnea occurred in the subject during sleep.

FIG. 2A is a diagram showing the CSI according to the embodiment of the present invention, in which the curve 21 represents the CSI. As can be seen from FIG. 2A, there may be an offset between the CSI in the time zone R1 and the CSI in the time zone R2. This offset can occur due to different sleep states. To eliminate this offset, the detection module 123 can calculate the first derivative signal corresponding to the CSI. FIG. 2B is a diagram of the first-order differential signal according to the embodiment of the present invention, in which case the curve 23 represents the first-order differential signal. As can be seen from FIG. 2B, there is no offset between the CSI in the time zone R1 and the CSI in the time zone R2.

In one embodiment of the invention, the detection module 123 may be configured to generate a filtering signal corresponding to the CSI by a filtering algorithm before computing the first derivative signal. FIG. 2C is a diagram showing a filtering signal according to an embodiment of the present invention, in which case the curve 22 represents this filtering signal. The detection module 123 can generate a first-order differential signal by differentiating the filtering signal after the filtering signal is generated. Filtering algorithms can be associated with moving average filtering, high pass filtering, low pass filtering, or band pass filtering, but this invention should not be considered limiting to this.

In one embodiment of the present invention, the detection module 123 can generate the first-order differential signal and then correct the outliers in the first-order differential signal to generate the corrected first-order differential signal. .. FIG. 2D is a diagram showing the corrected first-order differential signal according to the embodiment of the present invention, in which case the curve 23 represents the uncorrected first-order differential signal. The detection module 123 can generate an upper limit value ub and a lower limit value lb according to the median value m of the first-order differential signal. For example, the upper limit ub can be equal to the sum of the median m of the first derivative signal and the standard deviation of the first derivative signal, and the lower limit lb is the standard of the first derivative signal from the median m of the first derivative signal. It can be equal to the difference obtained by subtracting the deviation. Therefore, the detection module 123 can determine a data point larger than the upper limit value ub or smaller than the lower limit value lb in the first-order differential signal as an outlier. As shown in FIG. 2D, the detection module 123 can determine the data point PA smaller than the lower limit value lb as an outlier.

The detection module 123 can correct outliers in the first-order differential signal to generate the corrected first-order differential signal. In one embodiment of the invention, the detection module 123 may replace the outliers with the median m so that the corrected data point PA is the same as the median m. In one embodiment of the invention, the detection module 123 performs interpolation calculations on the data point PB before the data point PA and the data point PC after the data point PA in the first derivative signal to correct the outliers. Can be done. The correction value of the data point PA can be equal to the interpolation calculation result of the data point PB and the data point PC.

FIG. 3 is a diagram for acquiring the maximum value of the frequency response according to the embodiment of the present invention, in which case the curve 24 represents the first derivative signal (or the corrected first derivative signal). The detection module 123 can generate a plurality of frequency responses corresponding to the first-order differential signal, in which case the plurality of frequency responses correspond to a plurality of time points, respectively. For example, the detection module 123 can apply a window function 31 to perform a Fourier transform on a portion 25 of the first derivative signal corresponding to time point t1, in which case the frequency response can be represented by a curve 26. The detection module 123 can further acquire the maximum value m1 corresponding to the frequency response at time point t1. The detection module 123 can acquire a plurality of maximum values corresponding to the frequency response by executing the same steps. As shown in FIG. 4, the detection module 123 can generate the maximum value curve 27 corresponding to the reference time zone T1 according to the maximum value and the time point corresponding to these maximum values.

FIG. 4 is a diagram for determining the occurrence of the apnea phenomenon based on the maximum value according to one embodiment of the present invention, in which case the maximum value curve 27 includes the maximum value corresponding to a plurality of time points. Can be done. For example, this maximum value curve 27 can have a maximum value m1 corresponding to a time point t1. The detection module 123 can detect the phenomenon of apnea according to the maximum value curve 27. In particular, the detection module 123 can extract the reference time zone T2 from the reference time zone T1 according to the threshold value TH. This reference time zone T2 corresponds to a subset of the maximum values in the maximum value curve 27, where each of the maximum values in this subset is smaller than the threshold TH. As shown in FIG. 4, during the reference time zone T2, each of the maximum values of the maximum value curve 27 is smaller than the threshold value TH.

The detection module 123 can determine whether or not the reference time zone T2 is longer than the apnea time zone after obtaining the reference time zone T2. If the reference time zone T2 is longer than the apnea time zone, the detection module 123 can determine that the apnea phenomenon has been detected. Therefore, the detection module 123 can generate a detection result indicating the occurrence of the apnea phenomenon. The apnea time zone can be set by the user of the electronic device 100. For example, the user can set the apnea time zone to 10 seconds according to the definition of apnea in the medical community.

The threshold TH can be generated by the detection module 123. In particular, the detection module 123 may arrange the maximum values in the maximum value curve 27 from the smallest to the largest to generate the maximum value column 28. Next, the detection module 123 can select the Nth maximum value from the maximum value column 28 as the threshold value TH. The detection module 123 can acquire N according to the following equation (1), in which T is the apnea time zone, T1 is the reference time zone, and K is the maximum number of values. (That is, the maximum value column 28 has K maximum values).

FIG. 5 is a diagram for moving the head of a subject using the air cushion 300 according to the embodiment of the present invention. The subject can place the air cushion 300 at the bottom of the pillow 400. If the detection module 123 determines that the apnea phenomenon has occurred in the subject, the air cushion control module 125 can inflate the air cushion 300 by setting the air pump 200 to pass through the transceiver 130. The air cushion 300 may lift the pillow 400, thereby lifting the subject's head 500 to secure the subject's airway. This can prevent the occurrence of the apnea phenomenon.

FIG. 6 is a flow chart showing an apnea detection method according to an embodiment of the present invention, and this method can be achieved by the electronic device 100 shown in FIG. In step S601, a radio signal is transmitted to the subject, an echo corresponding to the radio signal is received, and CSI is acquired from this echo. In step S602, a detection result is generated according to the CSI, and the detection result indicates whether or not the phenomenon of apnea has occurred in the subject. In step S603, the detection result is output.

In short, the electronic devices provided in one or more embodiments of the invention can be applied to detect CSI without contact with the subject, yet determine if the phenomenon of apnea is occurring in the subject. be able to. There may be offsets during the subject's sleep time (eg, offsets that may occur due to different sleep states and may adversely affect detection results). In response to this offset, the CSI may be identified to eliminate the offset according to one or more embodiments of the invention. As achieved in one or more embodiments of the invention, the frequency response can act to determine if an apnea phenomenon is occurring. When the phenomenon of apnea occurs, the subject's head is lifted by applying an air cushion in one or more embodiments of the invention to widen the subject's airway, thereby avoiding the occurrence of respiratory arrest. Can be done. Thus, in one or more embodiments of the invention, it is possible to monitor whether or not a phenomenon of apnea has occurred in a subject and, in addition, improve the quality of sleep of the subject.

As will be apparent to those skilled in the art, various modifications and variations can be made to the embodiments described above. The above and embodiments are merely exemplary, and the true scope of the invention is represented by the following claims and their equivalents.

The electronic device of the present invention may be applied to a smart inflatable pillow (inflated smart pillow) or a smart mattress.

100: Electronic device 110: Processor 120: Storage medium 121: Data acquisition module 122: Subcarrier selection module 123: Detection module 124: Output module 125: Air cushion module 130: Transceiver 200: Air pumps 21, 22, 23, 24, 26: Curve 25: Part of the first derivative signal 27: Maximum value curve 28: Maximum value column 300: Air cushion 31: Window function 400: Pillow 500: Head
lb: lower limit m: median
m1: Maximum value PA, PB, PC: Data points R1, R2: Time zone S601, S602, S603: Step
t1: Time point T1, T2: Reference time zone TH: Threshold
ub: Upper limit

Claims (20)

Transceiver and
A storage medium that stores multiple modules and
A processor coupled to the storage medium and the transceiver to access and execute the plurality of modules.
It is an apnea detection electronic device equipped with
The plurality of modules
A data acquisition module that transmits a radio signal to a subject via the transceiver, receives an echo corresponding to the radio signal via the transceiver, and acquires channel state information from the echo.
A detection module that generates a detection result according to the channel state information and causes the detection result to indicate whether or not the subject is experiencing an apnea phenomenon.
It includes an output module that outputs the detection result via the transceiver.
Apnea detection electronic device. The apnea detection electronic device according to claim 1.
The apnea detection electronic device further
With an air cushion,
It is equipped with an air pump that is connected to the air cushion and communicates with the transceiver.
The module further
It comprises an air cushion control module that inflates the air cushion by configuring the air pump to navigate through the transceiver in response to the phenomenon of apnea.
Apnea detection electronic device. The apnea detection electronic device according to claim 1.
The detection module further
The first-order differential signal corresponding to the channel state information is calculated, and the first-order differential signal is calculated.
The first-order differential signal is configured to detect the apnea phenomenon.
Apnea detection electronic device. The apnea detection electronic device according to claim 3.
The detection module further
A filtering signal corresponding to the channel state information is generated by a filtering algorithm.
It is configured to differentiate the filtering signal to generate the first derivative signal.
Apnea detection electronic device. The apnea detection electronic device according to claim 4, wherein the filtering algorithm is associated with at least one of moving average filtering, high-pass filtering, low-pass filtering and bandpass filtering. .. The apnea detection electronic device according to claim 3.
The detection module further
A plurality of frequency responses corresponding to the first-order differential signal are generated, and the plurality of frequency responses correspond to a plurality of time points, respectively.
Obtaining a plurality of maximum values corresponding to each of the plurality of frequency responses,
The plurality of maximum values generate a maximum value curve corresponding to the first reference time zone, and the first reference time zone has the plurality of time points.
The maximum value curve is configured to detect the phenomenon of apnea.
Apnea detection electronic device. The apnea detection electronic device according to claim 6.
The detection module further
A second reference time zone is extracted from the first reference time zone according to a threshold value, and the second reference time zone corresponds to a subset of the plurality of maximum values in the subset. Each of the plurality of maximum values is smaller than the threshold value,
It is configured to determine that the phenomenon of apnea is detected in response to the second reference time zone being longer than the time zone of apnea.
Apnea detection electronic device. The apnea detection electronic device according to claim 7.
The detection module further
Arrange the plurality of maximum values from the smallest to the largest to generate a column of maximum values.
The Nth maximum value from the maximum value column is selected as a threshold value, and N is the product of the ratio of the apnea time zone to the first reference time zone and the number of the plurality of maximum values. Configured to
Apnea detection electronic device. The apnea detection electronic device according to claim 6.
The detection module further
The upper limit value and the lower limit value are generated according to the median value of the first-order differential signal, and the upper limit value and the lower limit value are generated.
A data point larger than the upper limit value or smaller than the lower limit value in the first-order differential signal is determined as an outlier.
It is configured to correct the outliers to generate a corrected first-order differential signal and to generate the plurality of frequency responses according to the corrected first-order differential signal.
Apnea detection electronic device. The apnea detection electronic device according to claim 9.
The detection module is
The step of replacing the outliers with the median,
Interpolation calculations are performed on the first data point before the data point and the second data point after the data point to correct the outliers, and the first data point and the second data point are described. Correcting the outliers according to one of the steps to be included in the first derivative signal.
Apnea detection electronic device. A step of transmitting a radio signal to a subject, receiving an echo corresponding to the radio signal, and acquiring channel state information from the echo.
A step of generating a detection result according to the channel state information and indicating whether or not the apnea phenomenon is occurring in the subject based on the detection result.
The step to output the detection result and
Apnea detection method having. The apnea detection method according to claim 11 further comprises.
An apnea detection method comprising the steps of configuring an air pump to inflate the air cushion in response to the apnea phenomenon. The apnea detection method according to claim 11.
The step of generating the detection result according to the channel state information is
The step of calculating the first-order differential signal corresponding to the channel state information,
The step of detecting the apnea phenomenon in response to the first-order differential signal, and
A method for detecting apnea. The apnea detection method according to claim 13.
The step of calculating the first derivative signal corresponding to the channel state information is
A step of generating a filtering signal corresponding to the channel state information by a filtering algorithm, and
The step of differentiating the filtering signal to generate the first-order differential signal,
A method for detecting apnea. The apnea detection method according to claim 14.
The filtering algorithm is an apnea detection method associated with at least one of moving average filtering, high pass filtering, low pass filtering and band pass filtering. The apnea detection method according to claim 13.
The step of detecting the apnea phenomenon in response to the first-order differential signal is
A step of generating a plurality of frequency responses corresponding to the first-order differential signal, and the plurality of frequency responses corresponding to a plurality of time points, respectively.
The step of acquiring a plurality of maximum values corresponding to each of the plurality of frequency responses, and
A step in which a maximum value curve corresponding to the first reference time zone is generated according to the plurality of maximum values, and the first reference time zone has the plurality of time points.
The step of detecting the apnea phenomenon according to the maximum value curve, and
A method for detecting apnea. The apnea detection method according to claim 16.
The step of detecting the apnea phenomenon according to the maximum value curve is
A second reference time zone is extracted from the first reference time zone according to a threshold value, and the second reference time zone corresponds to a subset of the plurality of maximum values in the subset. A step in which each of the plurality of maximum values is smaller than the threshold value,
A step of determining to detect the apnea phenomenon in response to the second reference time zone being longer than the apnea time zone.
A method for detecting apnea. The apnea detection method according to claim 17.
The step of detecting the phenomenon of apnea according to the maximum value curve further
The step of arranging the plurality of maximum values from the smaller one to the larger one to generate a column of maximum values, and
The Nth maximum value from the maximum value column is selected as a threshold value, and N is the product of the ratio of the apnea time zone to the first reference time zone and the number of the plurality of maximum values. A method for detecting apnea, which has steps to be performed. The apnea detection method according to claim 16.
The step of generating the plurality of frequency responses corresponding to the first derivative signal is
A step of generating an upper limit value and a lower limit value according to the median value of the first-order differential signal, and
A step of determining as an outlier a data point larger than the upper limit value or smaller than the lower limit value in the first-order differential signal.
An apnea detection method comprising a step of correcting the outliers to generate a corrected first-order differential signal and generating the plurality of frequency responses in response to the corrected first-order differential signal. The apnea detection method according to claim 19.
The step of correcting the outliers and generating the corrected first derivative signal is
The step of replacing the outliers with the median,
Interpolation calculations are performed on the first data point before the data point and the second data point after the data point to update the outliers, and the first data point and the second data point are described. The steps included in the first-order differential signal and
An apnea detection method having one of the steps.

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